如何使用数据:回归基于理解的深度学习和测评——访国际知名学习科学专家戴维·谢弗

How to Use Data Scientifically?Returning to Theory-based Deep Learning and Assessment:An Interview with Prof. David Williamson Shaffer

大数据时代的到来,给学习科学研究人类的学习及如何促进深度学习提供了机遇,但也存在一种迷思,即当我们拥有了海量数据,在不了解数据背后含义的前提下,就能依靠统计方法发现以往无法发现的有意义模式,提供智能化的教学建议,甚至实现智慧教育。单纯依靠大数据驱动,真能实现对教与学变革的期待和目标吗?如何利用信息技术和教育大数据真正促进深度学习,并将深度学习和测评相联系?本期高阶访谈有幸邀请到国际知名学习科学专家戴维·谢弗(David Shaffer)教授分享他关于大数据时代下学习和测评的观点和经验。戴维·谢弗是美国威斯康星大学麦迪逊分校教育心理系学习科学研究讲席教授,哥本哈根奥尔堡大学学习分析研究客座教授和威斯康星州教育研究中心数据科学家,主要研究如何开发和评估复杂问题解决能力和协作思维技能。谢弗教授出版了《电脑游戏如何帮助孩子们学习》、《量化民族志》(Quantitative Ethnography)等专著,在《计算机与教育》《教育研究者》《教学科学》《思维、文化和活动》等国际知名期刊发表了百余篇游戏化学习、学习分析学术论文。

The coming of big data age brings opportunities for understanding how people learn and how to support deep learning.However,it also brings a misunderstanding to believe that,with huge volume of data,there is no need for understanding the meaning behind the data,but solely depending on statistical approaches to identify meaningful patterns that traditional educational research cannot find.Can we really achieve our expectations and goals of educational transformation based on the so-called big data driven approach?In this interview,we are pleased to invite Prof.David Williamson Shaffer,a well-known learning scientist to share his thoughts and experience in doing learning and assessment research in this big data age.David Williamson Shaffer is the Vilas Distinguished Achievement Professor of Learning Sciences at the University of Wisconsin in the Department of Educational Psychology.He is also the Obel Professor of Learning Analytics at Aalborg University in Copenhagen,and a Data Philosopher at the Wisconsin Center for Education Research.Professor Shaffer studies how to develop and assess complex and collaborative thinking skills.He is the author of How Computer Games Help Children Learn and Quantitative Ethnography.